Teaching | Robotic Instruments
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Available Courses
For more detailed information, click the plus sign (+) on the respective course.
Learning outcomes
On successful completion of this course, the student will be able to:
1. Present the general structure and principal implementation of embedded systems.
2. Describe the fundamental characteristics and associated design challenges of real-time systems.
3. Outline the central computer architecture concepts from the perspective of the real-time systems designer
4. Apply different memory technologies, input/output techniques, and peripherals for embedded systems.
5. Design embedded control hardware at the block diagram level for a specific application.
6.Program and evaluate preal-time embedded systems for a certain application.
Learning outcomes
After completing the course, a student can select a proper modelling approach for specific practical problems, formulate mathematical models of physical systems, construct models of systems using modelling tools such as MATLAB and Simulink, and estimate the parameters of linear and nonlinear static systems and linear dynamic systems from measurement data.
Learning outcomes
After completing the course, a student can:
1. explain the working principle of major micro- and nano robotic systems for different applications;
2. understand the physics of micro- and nano scale locomotion and interaction;
3. choose micro- and nano actuation techniques;
4. apply micro- and nano robotic manipulation systems for certain applications;
5. program and control micro- and nano robotic systems and
6. analyze and evaluate specific micro- and nano robotic implementations.
Available Majors
For more detailed information, click the plus sign (+) on the respective major.
Control, Robotics and Autonomous Systems major provides a strong basis in control engineering and automation, allowing a student then to specialize in a particular area of interest such as factory automation, robotics, smart systems, or industrial software systems. Central topics for all students include modelling, estimation and control of dynamical systems, as well as embedded systems and software for modern automation systems. Most courses include theory as well as its application in practice. Upon completion of the Major, the student will be able to:
- Understand the need for automation
- Design models and controllers for dynamical systems
- Analyze properties of and dynamics of systems
- Design industrial software applications
- Understand in-depth one of the focus areas (robotics, smart systems, control engineering, automation software, or factory automation)
AUS is a combination of computer science and electronic engineering. During the programme, students will gain new skills in both areas. In computer science, relevant skills include the Internet of Things (IoT), machine learning, artificial intelligence and robot vision. In electronic engineering, relevant fields are automation, control, embedded systems and communications. Students learn the latest theoretical knowledge and know-how to apply their skills in practical real-life problems. Typical application areas of autonomous systems include autonomous vehicles, intelligent robots, industrial IoT and autonomous software systems.
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